First, load necessary packages:

library(flexdashboard)
library(tidyverse)
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library(plotly)
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library(p8105.datasets)

Importing and cleaning the dataset:

data(ny_noaa)

ny_noaa_subset <- ny_noaa %>%
  filter(!is.na(prcp), !is.na(snow), !is.na(tmax), !is.na(tmin),date>="2010-01-01")

Scatter Plot (Precipitation per day in 2010)

plot_ly(ny_noaa_subset, x = ~date, y = ~prcp, type = "scatter", mode = "markers") %>%
  layout(title = "Date vs. Precipitation in 2010",
         xaxis = list(title = "Date"),
         yaxis = list(title = "Prcp"))

Pie Chart(Total precipitation per year)

agg_data <- aggregate(ny_noaa$prcp ~ format(ny_noaa$date, "%Y"), FUN=sum)

plot_ly(agg_data, labels = ~format(as.Date(ny_noaa$date, format="%Y-%m-%d"), "%Y"), values = ~ny_noaa$prcp, type = 'pie') %>%
  layout(title = 'Total Precipitation per Year')

Bar Chart(Snow amount in 2010 per location)

plot_ly(data = ny_noaa_subset, x = ~id, y = ~snow, type = 'bar', colors = 'viridis') %>%
  layout(title = "Snow amount in 2010 per location", xaxis = list(title = "location"), yaxis = list(title = "Snow amount"))